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--- |
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license: apache-2.0 |
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base_model: hZzy/qwen2.5-0.5b-sft-news-IFT |
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tags: |
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- alignment-handbook |
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- ndcg |
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- trl |
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- expo |
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- generated_from_trainer |
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- trl |
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- expo |
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- generated_from_trainer |
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datasets: |
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- hZzy/train_pairwise |
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model-index: |
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- name: qwen2.5-0.5b-expo-DPO-ES-1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/qhqu3qtk) |
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# qwen2.5-0.5b-expo-DPO-ES-1 |
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This model is a fine-tuned version of [hZzy/qwen2.5-0.5b-sft-news-IFT](https://huggingface.co/hZzy/qwen2.5-0.5b-sft-news-IFT) on the hZzy/train_pairwise dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3243 |
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- Logps: -83.2882 |
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- Logits: -0.6651 |
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- Objective: 2.2471 |
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- Dpo Loss: 2.2471 |
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- Regularize: 2.2471 |
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- Ranking Simple: 0.5378 |
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- Ranking Idealized: 0.5295 |
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- Ranking Idealized Expo: 0.5212 |
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- Wo Beta: 6.6815 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- gradient_accumulation_steps: 12 |
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- total_train_batch_size: 144 |
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- total_eval_batch_size: 12 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Logps | Logits | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo | Wo Beta | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:| |
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| 0.7017 | 0.1417 | 50 | 0.8470 | -93.0243 | -1.4582 | 0.8570 | 0.8570 | 0.8570 | 0.5238 | 0.5295 | 0.5212 | 7.8507 | |
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| 0.8112 | 0.2834 | 100 | 1.0529 | -86.6835 | -1.4382 | 1.0273 | 1.0273 | 1.0273 | 0.5285 | 0.5295 | 0.5212 | 7.4982 | |
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| 1.0895 | 0.4251 | 150 | 1.4497 | -84.4337 | -1.2965 | 1.4010 | 1.4010 | 1.4010 | 0.5321 | 0.5295 | 0.5212 | 7.2692 | |
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| 1.2363 | 0.5668 | 200 | 1.7035 | -77.7201 | -1.2956 | 1.6116 | 1.6116 | 1.6116 | 0.5321 | 0.5295 | 0.5212 | 7.2264 | |
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| 1.3152 | 0.7085 | 250 | 1.9222 | -92.7241 | -1.2565 | 1.8319 | 1.8319 | 1.8319 | 0.5311 | 0.5295 | 0.5212 | 7.1856 | |
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| 1.1899 | 0.8503 | 300 | 2.0298 | -90.9373 | -0.9785 | 1.9588 | 1.9588 | 1.9588 | 0.5367 | 0.5295 | 0.5212 | 6.9336 | |
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| 1.1443 | 0.9920 | 350 | 2.1654 | -82.1414 | -1.0214 | 2.0541 | 2.0541 | 2.0541 | 0.5435 | 0.5295 | 0.5212 | 7.0024 | |
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| 0.725 | 1.1337 | 400 | 2.2884 | -84.2526 | -0.7535 | 2.2360 | 2.2360 | 2.2360 | 0.5336 | 0.5295 | 0.5212 | 7.1525 | |
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| 0.7629 | 1.2754 | 450 | 2.1606 | -80.4165 | -0.8866 | 2.0671 | 2.0671 | 2.0671 | 0.5321 | 0.5295 | 0.5212 | 6.7949 | |
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| 0.8044 | 1.4171 | 500 | 2.2094 | -82.3927 | -0.7503 | 2.0981 | 2.0981 | 2.0981 | 0.5347 | 0.5295 | 0.5212 | 6.8050 | |
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| 0.7105 | 1.5588 | 550 | 2.1697 | -84.9780 | -0.6734 | 2.0733 | 2.0733 | 2.0733 | 0.5321 | 0.5295 | 0.5212 | 6.8722 | |
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| 0.6925 | 1.7005 | 600 | 2.1957 | -81.5342 | -0.7411 | 2.0558 | 2.0558 | 2.0558 | 0.5357 | 0.5295 | 0.5212 | 6.7186 | |
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| 0.6883 | 1.8422 | 650 | 2.2080 | -82.7303 | -0.6908 | 2.1330 | 2.1330 | 2.1330 | 0.5383 | 0.5295 | 0.5212 | 6.8081 | |
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| 0.6486 | 1.9839 | 700 | 2.3243 | -83.2882 | -0.6651 | 2.2471 | 2.2471 | 2.2471 | 0.5378 | 0.5295 | 0.5212 | 6.6815 | |
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| 0.3793 | 2.1256 | 750 | 2.2675 | -84.2296 | -0.7879 | 2.1825 | 2.1825 | 2.1825 | 0.5409 | 0.5295 | 0.5212 | 6.8794 | |
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| 0.3314 | 2.2674 | 800 | 2.2106 | -84.3675 | -0.6651 | 2.1041 | 2.1041 | 2.1041 | 0.5414 | 0.5295 | 0.5212 | 6.7463 | |
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| 0.3301 | 2.4091 | 850 | 2.2964 | -84.8913 | -0.6177 | 2.2221 | 2.2221 | 2.2221 | 0.5388 | 0.5295 | 0.5212 | 6.8020 | |
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| 0.3509 | 2.5508 | 900 | 2.2796 | -84.3833 | -0.6097 | 2.2099 | 2.2099 | 2.2099 | 0.5393 | 0.5295 | 0.5212 | 6.7934 | |
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| 0.321 | 2.6925 | 950 | 2.3403 | -83.2967 | -0.7158 | 2.2649 | 2.2649 | 2.2649 | 0.5331 | 0.5295 | 0.5212 | 6.8864 | |
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### Framework versions |
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- Transformers 4.42.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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